1. Field of Invention
The invention is related to mapping the hydrocarbon reservoir formations that display dynamic elastic nonlinearity to the seismic signals, which propagate through them. The main reason for this nonlinear behavior in the reservoir rocks is their bulk rock property: the porosity, fractures, grain-to-grain contacts and the pore fluids. The measurements of the interaction of the two seismic waves as they propagate through the elastically nonlinear formations of a reservoir are used to measure their bulk rock properties.
2. Description of the Prior Art
The current state-of-the-art seismic technologies that are being used to map the reservoir characteristics include 3-D seismic reflection surveys, seismic attribute analysis, signal amplitude extraction and coherency techniques. In spite of all the recent progress in seismic data acquisition and seismic data processing, results are quite often non-unique and ambiguous and fail to identify the higher porosity and fractured zones that contain a major portion of the hydrocarbon reserves.
New technologies and more sensitive methods of measuring the reservoir characteristics have to be developed and introduced to identify and map the higher porosity and fractured reservoir rocks, which may contain unproduced hydrocarbon reserves. In the past, the seismic industry has ignored the effects of elastic dynamic nonlinearity of the reservoir rocks. The measurement of the dynamic elastic nonlinearity of the rock is a sensitive tool because the porosity induces an orders of magnitude change for the nonlinear coefficients and a few percent change for linear parameters (velocity, attenuation etc.). Ref: Donskoy, McKee (1977); Paul Johnson (1997).
The dependence of the dynamic elastic nonlinear parameters of the rock on its bulk porosity and its fluid content has an important practical application. The correlation between the measurable effective nonlinear parameters and the structural parameters of the porous and fractured media can be used as a diagnostic tool for reservoir characterization. The measurement of elastic nonlinearity of the reservoir formations using seismic waves directly correlates with its bulk porosity, micro-fractures and the fluid content.
Two compressional waves, as they propagate through a porous rock that acts as an elastically nonlinear medium, interact with each other. Due to this interaction, the sum and difference frequencies of the two primary waves are created. These new frequencies constitute an xe2x80x98interactionxe2x80x99 wave that travels along with the primary waves. The amplitude of the summed frequencies or the xe2x80x98interactionxe2x80x99 wave is a function of the amplitudes of the two primary waves and the propagation distance through the nonlinear rock. The amplitude of the xe2x80x98interactionxe2x80x99 wave is proportional to the product of the primary wave amplitudes. Its amplitude grows with propagation distance due to nonlinearity and decays with distance due to attenuation. Reference U.S. Pat. No. 6,175,536 (Khan), where the interaction of the two crosswell seismic signals was successfully recorded as they propagate through the nonlinear reservoir formations.
This invention uses the measurement of the summed and differenced frequencies that are created due to the interaction of the two seismic (waves) or signals as they propagate through the porous and heterogeneous reservoir rocks. One of the signals is a vibratory xe2x80x98sweepxe2x80x99 commonly used for seismic recording; the frequency is swept over the seismic band from low to high or high to low over a period of several seconds. The concept is well known in the industry and is the current art.
The second signal is a mono-frequency sinusoidal signal, which has the same time duration as the vibratory sweep. Both the seismic signals or waves are generated, and transmitted using standard vibratory sources from a single source array, that behave as a single surface source location. The combined seismic wave is used for seismic reflection recording. It propagates through the surface formations and is transmitted and reflected at the formation boundaries that provide acoustic impedance contrasts. The reflected seismic signals are recorded using multiple detector arrays, located on the surface or in different well bores or both. The recording procedures are known in the current art.
In this invention, the interaction of the two-seismic waves as they propagate through the reservoir rocks is measured to map their nonlinear characteristics that correspond due to their bulk porosity, heterogeneity, and fluid contents. The data, which are recorded, have two different sets of information. The cross-correlation with the standard xe2x80x98sweepxe2x80x99 provides the normal data-set that is used for normal reflection processing similar to current 2-D and 3-D seismic processing that is universally practiced and known in the art. The second set of information is extracted, by generating two new sweep signals. These new signals are generated by adding and differencing the mono-frequency with the xe2x80x98sweepxe2x80x99 frequencies, thus providing two xe2x80x98modified-sweepsxe2x80x99 and cross-correlating the recorded data with these xe2x80x98modified-sweepsxe2x80x99.
This new set of data, which results after cross-correlation with the two xe2x80x98modified-sweepsxe2x80x99 and contains newly generated frequencies, represents the result of interaction between the mono-frequency wave and the xe2x80x98sweepxe2x80x99 frequency wave, as they propagate through the nonlinear reservoir rocks. The processing parameters for this new data-set are similar to the parameters used for the data generated after cross-correlation with the primary xe2x80x98sweepxe2x80x99 signal. Conventional 2-D and 3-D seismic processing sequence can be used for both sets of data to provide the reflection seismic image of the subsurface. The integration and interpretation of the two results, one based on the primary sweep, and the other based on the two modified-sweeps, highlights and identifies the subsurface formations that are nonlinear due to porosity, microfractures and fluid saturation. The results based on the two xe2x80x98modified-sweepsxe2x80x99 will display the reflected signals from higher porosity and micro-fractured formations at relatively higher amplitudes compared to the reflections from homogeneous and non-porous formations.
The unique contribution of this invention is that it provides a method of differential illumination of the subsurface formations that are of greater interest to the hydrocarbon producers. Clays and shales are normally less porous, more homogeneous and behave more linearly in comparison with high porosity sandstones and limestones. As a result, shales and clays generate a weaker xe2x80x98interactionxe2x80x99 signal and will show less prominent response on the nonlinearity seismic section.
The seismic results based on the second data-set that are produced after correlation with the two xe2x80x98modified-sweepsxe2x80x99 identify and high light the zones that have higher nonlinearity due to higher porosity, microfractures or their fluid content, thus identifying the formations that have greater potential for increasing the hydrocarbon reserves.
Briefly, the present invention provides a new and improved method of mapping the subsurface formations that are heterogeneous, that have higher porosity or that have fractures. Two surface vibratory sources are used: (a) One surface source that transmits a conventional sweep, where the frequencies in the seismic bandwidth are swept from low to high or high to low; and (b) the other surface source generates a mono-frequency sinusoidal signal that is predetermined. Both sources transmit their signals from the same source location, and their start timings are synchronized.
The simultaneous transmission of the mono-frequency and the swept signal generates a combination of two waves that travel through the earth formations, and are reflected and refracted from the acoustic boundaries as they propagate through the earth. The reflected signals are recorded by the seismic detectors that are located on the surface, ocean bottom, in one or more well bores or any different combinations of above.
Since all earth formations exhibit certain amount of elastic nonlinearity, the two seismic signals (waves) interact with each other as they propagate through different formations. The level of interaction between the two seismic waves directly relates to the order of nonlinearity that exists in each subsurface formation.
The degree of elastic nonlinearity in different earth formations changes according to the rock properties, the presence of compliant features, and the pore fluids. The porous rocks and the fractured rocks exhibit a higher order of elastic nonlinearity due to disorganized and larger pore space. Shales and clays, compared to sands, exhibit lower order of nonlinearity since they are more homogeneous and have lower porosity.
The level of interaction between the two seismic waves is greater in higher porosity and micro-fractured rocks. Due to this reason, new frequencies that result from the nonlinear interaction have larger amplitude in higher porosity and micro-fractured rocks compared to non-porous rocks. These new frequencies are generated by a continuous process of summing and differencing, between the two frequencies of the primary signals, as the two signals propagate through nonlinear formations. The interaction of the mono-frequency with the swept frequency signal generates two sets of swept frequencies. One is the result of addition and the other of subtraction; these two new signals can be identified as xe2x80x98interaction-sweepsxe2x80x99 or xe2x80x98modified sweepsxe2x80x99.
For every set of recording, where both the mono-frequency surface source and the swept frequency source have been activated, three sets of data are collected, processed and interpreted. The first one is the conventional dataset generated by the cross-correlation of the recorded data with the standard swept frequency signal, that is used for the 2-D and 3-D seismic processing, and is well known in the art. The other two data-sets, that result after cross-correlation with the xe2x80x98modified sweepsxe2x80x99 (amended), are unique since they represent newly generated frequencies that have been created due to the nonlinearity of the earth""s formations.
The cross-correlation function is a measure of similarity between two data sets. The corresponding values of the two data sets are multiplied sample by sample and the products summed to give the value of the cross-correlation. Wherever the two signals match, the products are positive and the result of the cross-correlation is very large. However when the two signal do not match and some of the samples are of opposite phase and some in phase with each other, some of the products are negative and some positive, thus reducing the end sum to a much smaller value. For the cross-correlation of the field record, the sweep signal is aligned in time with the field record at zero time, and cross-correlated. After that the sweep is moved in time by one digital sample and the two signals are cross-correlated again. Each cross correlation gives one sample of the cross-correlated result. The process of time shifting the sweep and cross-correlating it with the field record continues until the required length of the cross-correlated field record has been achieved. The process of cross-correlation can also be performed in frequency domain. In frequency domain cross-correlation is equivalent to multiplying the amplitude spectra and subtracting the phase spectra. The process of cross-correlation is a powerful matching-filter and eliminates any signals that do not match the xe2x80x98sweepxe2x80x99 signal. The attenuation of the undesired signals is usually better thanxe2x88x9240 Db. (100:1). For this reason, the method described in this Application relies on the process of cross-correlation to totally separate the reflections resulted from the swept frequency xe2x80x98sweepxe2x80x99 signal and the reflections which result from the interaction between the xe2x80x98sweepxe2x80x99 and the xe2x80x98mono-frequencyxe2x80x99 signals.
The two new sets of data are processed using similar processing parameters as the conventional 2-D and 3-D seismic reflection data, which is known in the art. These reflection-seismic results, that contain newly generated frequencies, emphasize the presence and locations of the high porosity and fractured formations in comparison with the formations that are non-porous like shales and clays.
In the real world situation, it is difficult to identify a universal data processing sequence for 2-D or 3-D seismic, since the choice of the data processing parameters depends a great deal on the signal to noise ratio of the recorded data, near surface problems of the survey area, and the velocity model of the subsurface being mapped. The data processing technology has matured to the degree that most data processing centers have the knowledge to process the 2-D or 3-D seismic data, which have been recorded in different geologic environments with similar results. We can say that data processing sequences are readily available in the industry to provide satisfactory results for most of the surface and geologic conditions that we try to image. There is current knowledge in the industry to process the data for the method described in the Application.
During the 50 years of research and development in seismic data processing, a lot of new software routines and processing algorithms have been developed. However in spite of all the progress, the fundamental issues and the goals of seismic data processing have remained the same. The end result of the total seismic effort, acquisition and processing is to develop an accurate geologic model of the subsurface rock formations in true depth, map the rock properties to identify the porosity, permeability and fracturing, and to map the pore fluids that saturate the reservoir rocks. The universal challenges that have faced the industry over this time have also remained the same:
How to improve the signal to noise ratio, so that the reliability of the processed results can be improved. The xe2x80x98noisexe2x80x99 is defined as any unwanted signal and includes random noise, organized noise, multiples, converted waves etc.
For surface seismic, surface and near surface problems have been a major challenge, which include the coupling response of the sources and receivers, static time corrections due to changes in the thickness and the velocities of the near surface weathering layers, attenuation of higher frequencies; all these factors degrade the data quality and affect the final seismic image. To get an accurate seismic velocity model of the area to be mapped is another challenge, since the depth conversion can only be valid when exact velocities are used during data processing and seismic imaging.
Complex subsurface structures with conflicting dips and abrupt discontinuities make the seismic imaging difficult since the seismic wave paths get distorted.
Anisotropy of the seismic wave field provides additional challenges that data processing has to overcome.
Additional seismic attributes are needed to accurately map the reservoir properties.
For the reasons described above, the processing flow of the seismic data changes according to the geologic objectives. However, the seismic data processing has become a matured science. Most data processing centers around the world have similar capabilities, similar software and processing routines. The data processing has matured to the point that most of the software products have been standardized and practically all the major processing centers can provide very similar seismic images of the subsurface geology.
There are certain important considerations for processing the data recorded according to the method described in the Application:
The interaction-wave, which results due to elastic nonlinearity of the porosity in the subsurface rocks, follows the same reflection and refraction laws as the primary xe2x80x98sweepxe2x80x99 signal, as a result the data processing parameters, which are related to static and dynamic corrections, have to be identical for both the data sets.
The data processing sequence and the selection of the processing algorithms is determined by the primary data, which is the result of the cross-correlation with the primary xe2x80x98sweepxe2x80x99 signal. The xe2x80x98sweepxe2x80x99 signal is the signal transmitted by the surface seismic vibrator and acts as a primary source.
During the pre-processing or primary processing sequence, the standard processing routines of spherical divergence correction, attenuation of source generated noise, surface consistent amplitude balancing, de-convolution, etc. are applied.
Velocity analysis is done for determining the seismic velocities for migration or CDP stack.
Surface consistent static corrections applied, followed by residual static corrections.
Post stack or pre-stack migration is performed.
Coherency enhancement applied if necessary.
The processing sequence is repeated for the data generated after cross-correlation with the xe2x80x98modified sweepxe2x80x99 signals, which resulted after the sum and difference of the xe2x80x98sweepxe2x80x99 signal with the mono-frequency signal. The same processing parameters are used, which were derived based on the primary xe2x80x98sweepxe2x80x99 data that include static and dynamic corrections along with other data enhancement routines used previously to process the primary data, which resulted after cross-correlation with the xe2x80x98modified sweepxe2x80x99 signals.
Reflection images of all the three data sets, which result after data processing are used for interpreting the subsurface porosity.
Integration and interpretation of the processed reflection seismic results, based on the three sets of data, provide new and valuable information related to the reservoir and potential hydrocarbon accumulations. Data recorded by the downhole receivers, compared to the surface arrays, offer higher resolution. The higher resolution results due to the fact that the summed frequencies that are generated in the nonlinear reservoir rocks are less attenuated due to shorter return propagation distance.
The choices of applying this invention for reservoir characterization for different reservoirs will differ according to the production objectives and targets. In some areas, surface recording may provide the necessary information needed to map the reservoir characteristics, while in other areas it may be necessary to complement-the surface recorded data with the wellbore receiver data. Knowledge to modify and select the suitable recording and processing parameters for each individual case exists in the industry and is known in the art.